Experteer Overview In this role, you will design, build, and deploy FAIR-compliant data products that integrate diverse data across therapeutic areas to accelerate trials and ensure regulatory readiness. You will translate data roadmap requirements into scalable architectures and enable analytics, AI/ML, and automation. You’ll partner with data platform teams to operationalize products in cloud environments and ensure governance and quality. This role offers impact across Global Development and opportunities to shape data-driven decision making.Compensaciones / Beneficios
- Translate data product specifications into technical designs and deployments aligned with enterprise standards
- Develop APIs, ETL/ELT pipelines, and data integration layers linking internal and external datasets
- Ensure adherence to FAIR principles, semantic modeling, and the Global Development Ontology
- Collaborate with Data Platform teams to deploy products in cloud/hybrid environments (Azure, AWS, GCP)
- Integrate data from core Global Development systems (CTMS, EDC, eTMF, regulatory platforms, CRO datasets)
- Improve data flows for AI/ML readiness and predictive modeling use cases
- Implement automated validation, testing, and monitoring of data products
- Maintain documentation, version control, and audit-readiness practices
- Collaborate with governance teams to meet quality, metadata, and regulatory requirements
- Coordinate with Senior Manager, Data Strategy, Knowledge Management, and Regulatory Data Product Owner on shared use casesResponsabilidades
- Bachelor's or Master's in Computer Science, Data Engineering, Data Science, Biomedical Informatics, or related discipline
- 6+ years in data engineering or technical delivery within pharma/biotech, ideally in clinical development environments
- Proven track record building productized data assets integrated with enterprise data architectures
- Experience with cloud platforms (Azure Data Lake, AWS Redshift, GCP BigQuery)
- Experience with APIs and data integration technologies (Spark, Databricks, Kafka, etc.)
- Knowledge of semantic modeling, industry ontologies, and standards (CDISC, HL7 FHIR, TransCelerate DDF)
- Regulatory Data Product Owner experience in protocol metadata, submission readiness, and disclosure datasets
- Strong engineering mindset for scalable, resilient data solutions
- Proficient in modern data engineering tools and CI/CD pipelines
- Ability to collaborate across cross-functional teams and communicate technical concepts clearlyRequisitos principales
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